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DBMS > Citus vs. Google Cloud Datastore vs. Newts vs. Oracle NoSQL

System Properties Comparison Citus vs. Google Cloud Datastore vs. Newts vs. Oracle NoSQL

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNewts  Xexclude from comparisonOracle NoSQL  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTime Series DBMS based on CassandraA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes
Primary database modelRelational DBMSDocument storeTime Series DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Websitewww.citusdata.comcloud.google.com/­datastoreopennms.github.io/­newtswww.oracle.com/­database/­nosql/­technologies/­nosql
Technical documentationdocs.citusdata.comcloud.google.com/­datastore/­docsgithub.com/­OpenNMS/­newts/­wikidocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.html
DeveloperGoogleOpenNMS GroupOracle
Initial release2010200820142011
Current release8.1, December 201823.3, December 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache 2.0Open Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaJava
Server operating systemsLinuxhostedLinux
OS X
Windows
Linux
Solaris SPARC/x86
Data schemeyesschema-freeschema-freeSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.
Typing infopredefined data types such as float or dateyesyes, details hereyesoptional
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like query language (GQL)noSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
Java API
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC
C#
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App Enginenono
TriggersyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication using Paxosselectable replication factor infobased on CassandraElectable source-replica replication per shard. Support distributed global deployment with Multi-region table feature
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnoconfigurable infoACID within a storage node (=shard)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes infooff heap cache
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users and roles

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More resources
CitusGoogle Cloud DatastoreNewtsOracle NoSQL
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